Simple Image Search Engine

Demo

Workflow

News

• [2020.06] Updated many parts of the code for CVPR 2020 tutorial

Overview

• Simple image-based image search engine using Keras + Flask. You can launch the search engine just by running two python scripts.
• offline.py: This script extracts a deep-feature from each database image. Each feature is a 4096D fc6 activation from a VGG16 model with ImageNet pre-trained weights.
• server.py: This script runs a web-server. You can send your query image to the server via a Flask web-interface. The server finds similar images to the query by a simple linear scan.
• GPUs are not required.
• Tested on Ubuntu 18.04 and WSL2 (Ubuntu 20.04)

Usage

git clone https://github.com/matsui528/sis.git
cd sis
pip install -r requirements.txt

# Put your image files (*.jpg) on static/img

# Then fc6 features are extracted and saved on static/feature
# Note that it takes time for the first time because Keras downloads the VGG weights.
python offline.py

# Now you can do the search via localhost:5000
python server.py